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Rimini Street

Provides third-party enterprise software support

Agentic AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

  • 4–6 years of software engineering experience with strong Python and/or Java proficiency.
  • 3+ years of experience working with production AI/ML systems, including LLM-based applications.
  • 1+ years of experience designing or building agentic AI systems that reason, plan, use tools, and take actions.
  • Demonstrated experience with agent frameworks such as LangChain/LangGraph, Pydantic AI, CrewAI, AutoGen, Semantic Kernel, or equivalent.
  • Experience with tool-calling or function-calling patterns in LLMs, including MCP, OpenAI function calling, or Anthropic tool use.
  • Understanding of evaluation methodologies for non-deterministic systems and testing outputs that are not binary right or wrong.
  • Experience building systems with human-in-the-loop workflows and knowing when to pause for human judgment.
  • Advanced proficiency in Python; Pydantic AI is the primary agent framework and fluency is required.
  • Deep experience with Claude (Anthropic), GPT (OpenAI), or equivalent, including system prompts, tool calling, streaming, and structured output.
  • Hands-on experience with at least one agent framework: Pydantic AI, LangChain/LangGraph, CrewAI, or AutoGen, and ability to evaluate framework trade-offs.
  • Understanding of MCP tool definition, invocation patterns, and standardized protocols for agent interaction with external systems.
  • Understanding of A2A protocol and multi-agent communication patterns, including agent discovery, task delegation, and capability negotiation.
  • Understanding of RAG architecture, including vector search, reranking, context assembly, and citation.
  • Experience with agent evaluation frameworks such as TruLens, Ragas, or custom frameworks, including scenario-based, adversarial, and regression testing for agent behavior.
  • Understanding of durable execution (Restate/Temporal) and how agent reasoning integrates with workflow orchestration; ownership of Restate is assigned to the Platform Engineer, not this role.

Responsibilities

  • Design reasoning frameworks for agents to decompose complex ERP tasks into structured decision trees with governance checkpoints at each stage.
  • Build agent personas and behavioral profiles for Finance, Procurement, Supplier Management, Expense, and Support domains, defining domain-specific reasoning patterns, risk tolerances, and escalation triggers.
  • Architect dynamic tool-selection strategies that let agents choose MCP tools based on context, confidence, and task requirements rather than hardcoded sequences.
  • Design conversation-state management for long-running agent sessions spanning multiple interactions, tool calls, and human-in-the-loop approvals.
  • Build confidence-scoring frameworks that turn LLM output uncertainty into governance decisions: proceed, verify, escalate, or halt.
  • Design A2A communication patterns for collaborative workflows in which multiple specialized agents contribute to one business outcome.
  • Architect supervisor/worker agent hierarchies with delegation, progress monitoring, and result aggregation patterns.
  • Build conflict-resolution strategies for contradictory agent assessments.
  • Design shared context and memory patterns that let agent teams build collective understanding without redundant processing.
  • Translate OPA policy definitions into agent-actionable decision boundaries, bridging policy-as-code and agent reasoning.
  • Design the autonomy progression model, including how agents earn autonomy through demonstrated accuracy, lose trust after errors, and self-correct.
  • Build an explainability layer that enables agents to explain their reasoning chains to human reviewers in business-meaningful terms.
  • Design cognitive-level circuit breakers so agents recognize when they exceed their competence boundaries and proactively escalate rather than guess.
  • Design retrieval-augmented reasoning patterns that dynamically retrieve relevant knowledge from vector stores, historical and knowledge data, and approval-pattern databases.
  • Build feedback mechanisms that capture experienced users’ corrections or overrides of agent recommendations and use them to improve future reasoning.
  • Design agent-behavior evaluation frameworks covering reasoning quality, appropriate escalation, governance compliance, and user-trust metrics, in addition to output accuracy.
  • Build scenario-based testing methods using synthetic ERP scenarios to test agent behavior against edge cases, ambiguous situations, and adversarial inputs.
  • Define agent-performance metrics, including task completion rate, escalation accuracy, false positive and false negative rates for autonomous decisions, time to resolution, and user override frequency.
  • Own the continuous-improvement loop by analyzing production agent behavior, identifying reasoning failures, and refining cognitive architecture to prevent recurrence.

Desired Qualifications

  • Experience with ERP systems such as SAP, Oracle EBS, or JD Edwards; basic familiarity with accounts payable, general ledger, or procurement processes is valuable.
  • Java or Quarkus experience; ability to work across Python agents and a Java-native platform is an advantage.
  • Experience with reinforcement learning from human feedback (RLHF) or similar alignment techniques.
  • Knowledge graph design experience, including representing institutional knowledge as structured, queryable relationships.
  • Knowledge of formal decision theory or risk-assessment frameworks for designing autonomy governance.
  • Experience in regulated industries such as financial services, healthcare, or government, where AI systems must be explainable and auditable.
  • Technical writing experience documenting agent architectural decisions, reasoning patterns, and governance frameworks.

About the Company

Rimini Street

Provides third-party enterprise software support

Rimini Street provides third-party support and services for enterprise software from vendors like Oracle, SAP, VMware, Microsoft, and Salesforce, using subscription-based contracts. Its Rimini ONE offering can outsource the entire management of a company’s software stack, including customization support, at approximately half the vendor fees. The company differentiates itself with faster, more cost-effective service and a broad coverage that extends beyond basic maintenance to licensing advice and optimization. The goal is to help organizations extend the life of their existing software, reduce IT spend, and improve overall efficiency across mixed technology environments.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Las Vegas, NV
Founded
2005

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